基于人工神经网络的反射器型面精度预测

基于人工神经网络的预测方法,利用数量适当的有限元计算结果,建立人工神经网络模型,对反射器型面进行精度预测分析,得到在最小型面精度结果下的结构设计参数。计算结果显示训练好的神经网络模型能够较精确地预测格栅反射器的型面精度,节省计算时间,并且以型面精度最小为准则进行参数分析,能够指导反射器的结构设计。

Reflector Antenna Precision Prediction Based on Neural Network

The precision of reflector antenna on orbit is an important design specification,and the reasonable structure design can improve the reflector precision. By taking full advantages of the high strength,high modulus,low coefficient of thermal expansion of the composite material,and the surface precision of the antenna could be improve dsignificantly.By using the artificial neural networks highly nonlinear mapping capability,and based on the principle of the minimum RMS,the design parameters were optimized.The calculation results indicate that the computing time can be effectively saved. The results show that the optimization method is reasonable,and the structure design meets the design requirements. The design scheme and analytical methods provide a direction for the structure design of the reflector.